1. Field of the Invention
The invention relates to an apparatus and method for facilitating motion estimation on video signals. Such a method finds particular, but not exclusive, application in the field of motion compensated video format conversion (known as MC-VFC) and to 3-D recursive block matching techniques.
2. Description of the Related Art
Motion estimation generally comprises the following steps: 1) acquiring a number of candidate motion vectors; 2) calculating an error measure for each of these candidate motion vectors; and 3) selecting the best vector. This process is applied to all parts of the image. As this is generally a very computationally intensive task, many methods and strategies have been proposed to limit the number of candidates, while preserving a high accuracy and reliability of the calculated motion vectors.
A particularly effective searching arrangement suitable for MC-VFC is utilized in the 3-D Recursive Search Block matcher (3D-RS) described by G. de Haan et al. in “True motion estimation with 3-D recursive block-matching”, IEEE Trans. CSVT, October '93 pp. 368-388.
Motion estimation for scan rate conversion in a film mode comprises comparing image blocks of two frames (typically a previous frame and a current frame) to detect areas of similarity between the two successive frames, and where a high degree of similarity exists, the difference in the positions of the similar areas represents the motion vector. In video format conversion, the image data is then shifted over a part of the motion vectors to construct a frame of new (and previously non-existing) data which is temporally located between the two originally successive frames.
With video signals, a slightly more complex problem arises when such a format conversion is required, since video is usually broadcast in an interlaced format (one frame=2 fields, one field containing the odd lines and the next field containing the even lines of the frame). Here, the video sequence contains successive fields that contain vertically partitioned odd lines or even lines of a frame. Such an interlaced format may hamper the detection of similarity between image parts, as half of the lines are “missing”. This is particularly true for areas where there is “no motion”, as two successive fields (i.e., one with odd lines and one with even lines) cannot be directly compared with each other since they originate from different vertical positions in the image.
One partial solution to the above problem may be given by applying a de-interlacing algorithm. In such an algorithm, a received field may be electronically processed (for instance, by interpolation) so as to build a frame containing both odd and even lines, and the subsequently received field may then be compared to the corresponding lines in such a built-up frame. However, it will be appreciated that because such corresponding lines are the result of a calculation rather than naturally occurring, errors in the de-interlacing algorithm influence the quality of any “no motion” detection in the motion estimator.
U.S. Pat. No. 5,682,205 (Eastman Kodak Company) discloses a process and apparatus for generating a de-interlaced output image from a plurality of sequential interlaced image fields. According to this patent, fields of the same polarity (i.e., even/even or odd/odd) are always compared with one another to estimate motion. One consequence of this is that there is a relatively large “temporal distance” as compared fields are always non-consecutive.
U.S. Pat. No. 5,329,317 (Matsushita Electric Corporation of America) discloses an adaptive field/frame filter for interlaced video signals. In this disclosure, where there is a stationary image, frame filtering is preferentially applied, whereas for moving images or parts of images, field filtering is preferred. In this way, both field and frame filtering is done and the results are merged depending on the output of a motion detector. The motion detector always operates on a two-frame basis.